Inside Workday: The Data Science Intelligence Behind HiredScore

Transforming the Future of Talent Acquisition

Working on technology that solves hiring challenges is exciting. HR tech is still a relatively new and evolving field, so there are constantly new challenges, problems and opportunities that emerge as we understand more about people, companies and processes. We’re working on things that don’t yet exist, solutions that will end up shaping the future of talent acquisition and talent management.

HiredScore, recently acquired by Workday, leverages AI to improve hiring. Our AI-powered platform helps companies enhance efficiency, mitigate bias, and elevate the candidate experience when hiring. I’m excited to be a data scientist at Workday, especially during this time of rapid growth and innovation.

My team focuses on improving HiredScore, specifically the Spotlight and Fetch components that help companies find the right talent.

My team’s hallmark is our comprehensive project ownership; we’re fully engaged from initial concept to final implementation. We’re involved in every stage, from initial research and experimentation to implementing solutions and monitoring their impact in the market. This approach, coupled with a strong emphasis on making a difference, gives me a real sense of responsibility and accomplishment.

From Coding Roots to Data Routes: My Journey to Data Science

My passion for software and computers started early. I began coding in school and worked as a software developer during my time in the Army. I’ve explored various roles over the years, from becoming a scrum master to backend and iOS development. Eventually, I realised my passion for math and algorithms, which led me to transition into data science.

About seven years ago, I joined HiredScore, a small startup at the time with a team of around 25 people. I had the opportunity to work across its AI products and eventually became a team leader. I was consistently impressed by the ambition, innovation, and incredible people. Now part of Workday, I continue to appreciate the strong emphasis on values, including employee well-being and building impactful products that fuel innovation.

My Role as a Data Scientist

My role as a data scientist is like being a detective in the digital age. I dive into huge volumes of data, searching for patterns, insights, and hidden truths that can help organisations make informed decisions. I build the pipelines that channel this data, ensuring its quality and accessibility. Then, I craft and refine models, using statistical analysis and machine learning algorithms to unlock the narrative hidden within the numbers. It’s a constant process of experimentation, tweaking variables, testing hypotheses, and critically analysing the results, all while always striving for greater accuracy and efficiency.

But my job isn’t just about technical analysis. It’s about turning data into knowledge that drives action. Part of my role involves translating my findings into clear, compelling narratives, using visualisations and explanations that resonate with both technical and non-technical audiences. I bridge the gap between the complexities of large data sets and the human understanding of that data. And because the world of data science is ever-evolving, I’m a lifelong learner, constantly exploring new techniques and technologies to stay at the forefront of this exciting field.

Innovation in Action: Building Value at Workday

Unlike industries like Advertising Tech and FinTech, where AI and software solutions have been heavily invested in and the challenges are well-defined, HR Tech is still in its early stages. This means at Workday, we’re not just building solutions, we’re also defining the landscape. We’re figuring out the key performance indicators (KPIs), limitations, and best practices for this emerging field. It’s a unique opportunity that requires us all to constantly learn and adapt as we shape the future.

What makes my work fascinating is that we’re not just applying AI to existing problems; we’re defining the problems themselves. This is a rare opportunity in the AI world. It demands a deep understanding of cause-and-effect, a crucial skill for any data scientist.

My work involves reframing HR challenges as data science problems. This begins by identifying key metrics, pinpointing inefficiencies, and determining the necessary data. Once we have a clear picture, we develop the technology to address these challenges. This process of discovery and definition is both exciting and rewarding.

We use practical solutions in our approach to problem-solving, using a mix of cutting-edge machine learning algorithms and established techniques to achieve the best results. Our current tech stack includes tools like MongoDB and BigQuery for data analysis, and AWS SageMaker for model training and experimentation. We also write a lot of Python code to bring our models to life in production.

I find it rewarding to work at a company like Workday, dedicated to pushing the boundaries of HR tech. We’re driven by a desire to create impactful solutions that deliver value to our customers, and that passion fuels innovation. I’m excited to be part of this journey, contributing to the future of work where technology empowers both organisations and individuals in the world of work.

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